Learners should possess a fundamental knowledge of artificial intelligence concepts, including machine learning algorithms, data handling, and model evaluation.
A willingness to engage with complex concepts and explore advanced methodologies surrounding fairness, privacy-preserving techniques, and ethical considerations in AI is essential.
$44.99
Material Includes
Video Lesson
Handout Notes
Python Codes
MCQs
What I will learn?
Understand various methodologies and frameworks aimed at safeguarding data privacy in AI.
Gain a profound understanding of ethical frameworks in AI, exploring the ethical implications of algorithms, bias mitigation strategies, and the socio-cultural impact of AI applications.
Learn to identify and address biases within AI models.
Course Curriculum
From Privacy to Fairness in AI: Video Lesson
Current challenges in business for ML/AI
01:06:20
How to create fairness in AI?
02:29:49
Introduction to Privacy-Preserving ML/AI
02:08:41
Understanding the Ethics of AI
23:11
From Privacy to Fairness in AI: Handout Notes
Basic of Privacy to Fairness in AI/ML
Hands-on Implementation
Python Notebooks: Differential Privacy
Python Notebooks: Fairness Toolkit
Python Notebooks: Federated Learning
Python Notebooks: Encryption
Assessment
Self-Assessment
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